The present invention relates generally to broadcast systems. More particularly, the present invention pertains to methods of estimating the complexity of a series of images in compressed video programs that use MPEG compatible encoding.
In typical broadcast systems, such as in IPTV (Internet Protocol Television) and direct broadcast satellite (DBS) applications, multiple video programs are encoded in parallel, and the digitally compressed bitstreams are multiplexed onto a single, constant or variable bit rate channel. The available channel bandwidth could be distributed unevenly among programs, in proportion to the information content/complexity of each of the video sources. The monitoring system that computes video quality by measuring impairments could take into account the image complexity factor of the video stream to calculate the different effects of impairments on lesser or more complex images.
MPEG encoded variable bit rate (VBR) video traffic is expected to dominate the bandwidth of broadband networks. This could be delivered in streaming, on demand, IPTV or DBS types of environments. Accurate models of VBR or CBR video complexity is necessary to enable monitoring systems for prediction of performance of any proposed network during its operation. FIG. 1 shows components that are involved in delivering video content in a typical IPTV environment. Video source that originates as analog signal is encoded using an encoder and packetized and sent using an IP network. It could be sent as multicast or unicast to the network. The core contains various elements to provision and manage subscribers and traffic flows. The content is stored in content servers and delivered on demand upon user request. At various points in the network, measurements can be performed for impairments by service assurance managements systems.
MPEG coding standards define three picture types (I, B and P) and encodes pictures with a fixed arrangement. Picture type changes could occur due to scene transitions. In the event of an abrupt transition, the first frame of the new scene is intra-coded (I-frame) in order to avoid severe coding errors. During a gradual scene transition, the distance between two reference frames (I or P) can be changed to improve the picture quality. During most of these gradual transitions, temporal correlation tends to be reduced. This situation demands more frequent placement of predicted reference frames (P-frames) to uphold the required picture quality. When the video sequence contains rapid motions, this may also require frequent P-frames in order to improve picture quality. This increases the bit rate. On the other hand, if the scene does not contain any rapid motions or gradual scene transitions, the inter-frame (I-frame) reference distance can be increased without affecting the picture quality. This is due to the strong correlation between frames.
Accordingly, what is needed is a process to analyze the Video Coding Layer (VCL) complexity indication changes and bit rate changes in the video stream by analyzing VCL parameters including, but not limited to slice, macroblocks, quantization, INTER/INTRA coded reference and non-reference macroblock/slice/picture types and arrive at a statistical model to compute image complexity dynamically, so that impairment monitors could use this value to determine their effect on a sequence of complex images.